Bello Olalekan Akanji, Doguwa, Sani Ibrahim, Yahaya Abubakar, Jibril Haruna Mohammed
{"title":"二类半logistic指数威布尔分布的性质及其应用","authors":"Bello Olalekan Akanji, Doguwa, Sani Ibrahim, Yahaya Abubakar, Jibril Haruna Mohammed","doi":"10.56919/usci.2123.006","DOIUrl":null,"url":null,"abstract":"Recent research has demonstrated the utility of extending continuous distributions in fitting data of all kinds. This paper proposes the Type II Half-Logistic Exponentiated Weibull (TIIHLEtW) Distribution as a new distribution. For the Type II Half-Logistic Exponentiated Weibull distribution, we obtain precise expressions for the quantile function, probability-weighted, moments, moments generating function, reliability function, hazards function, and order statistics. The maximum likelihood estimation approach is used to estimate the parameters of the new distribution, and a simulation study is presented. Two real data sets are used to demonstrate the new distribution's applicability and flexibility. The findings indicated that the new distribution is a better fit for the data compared to the other models that were examined. \n ","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The properties of Type II Half-Logistic Exponentiated Weibull Distribution with Applications\",\"authors\":\"Bello Olalekan Akanji, Doguwa, Sani Ibrahim, Yahaya Abubakar, Jibril Haruna Mohammed\",\"doi\":\"10.56919/usci.2123.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent research has demonstrated the utility of extending continuous distributions in fitting data of all kinds. This paper proposes the Type II Half-Logistic Exponentiated Weibull (TIIHLEtW) Distribution as a new distribution. For the Type II Half-Logistic Exponentiated Weibull distribution, we obtain precise expressions for the quantile function, probability-weighted, moments, moments generating function, reliability function, hazards function, and order statistics. The maximum likelihood estimation approach is used to estimate the parameters of the new distribution, and a simulation study is presented. Two real data sets are used to demonstrate the new distribution's applicability and flexibility. The findings indicated that the new distribution is a better fit for the data compared to the other models that were examined. \\n \",\"PeriodicalId\":235595,\"journal\":{\"name\":\"UMYU Scientifica\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"UMYU Scientifica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56919/usci.2123.006\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"UMYU Scientifica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56919/usci.2123.006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The properties of Type II Half-Logistic Exponentiated Weibull Distribution with Applications
Recent research has demonstrated the utility of extending continuous distributions in fitting data of all kinds. This paper proposes the Type II Half-Logistic Exponentiated Weibull (TIIHLEtW) Distribution as a new distribution. For the Type II Half-Logistic Exponentiated Weibull distribution, we obtain precise expressions for the quantile function, probability-weighted, moments, moments generating function, reliability function, hazards function, and order statistics. The maximum likelihood estimation approach is used to estimate the parameters of the new distribution, and a simulation study is presented. Two real data sets are used to demonstrate the new distribution's applicability and flexibility. The findings indicated that the new distribution is a better fit for the data compared to the other models that were examined.